Creating a large-scale content-based airphoto image digital library

This paper describes a content-based image retrieval digital library that s upports geographical image retrieval over a testbed of 800 aerial photograp hs, each 25 megabytes in size. In addition, this paper also introduces a me thodology to evaluate the performance of the algorithms in the prototype sy stem. The major contributions of this paper are two. 1) We suggest an appro ach that incorporates various image processing techniques including Gabor f ilters, image enhancement, and image compression, as well as information an alysis technique such as self-organizing map (SOM) into an effective large- scale geographical image retrieval system. 2) We present two experiments th at evaluate the performance of the Gabor-filter-extracted features along wi th the corresponding similarity measure against that of human perception, a ddressing the lack of studies in assessing the consistency between an image representation algorithm or an image categorization method and human menta l model.